In the paper, we have conducted several simulation experiments in both low-dimensional and high-dimensional setups to illustrate the good performance of COMBSS in comparison to the existing popular methods: Forward Stepwise, Lasso, and Mixed Integer Optimization. These promising empirical results highlight the potential of COMBSS for feature extractions. We leave extensive performance comparisons with Lasso variants such as relaxed Lasso [1]} and best subset selection based on coordinate descent and local combinatorial optimization [2]} to future work.
